{"title":"Research on AUV Allocation Method Based on Optimization Algorithm","authors":"Zhang Hongqiang, Zeng Bin, Kang Jian","doi":"10.1109/CBFD52659.2021.00061","DOIUrl":null,"url":null,"abstract":"With the development of science and technology, the performance of autonomous underwater vehicles (AUV) has been continuously improved, and its application has become increasingly widespread, playing an important role in the military and civilian fields. AUV can perform underwater environmental reconnaissance, resource exploration, target search, and intelligence collection. In order to efficiently complete reconnaissance and search tasks, AUV resources need to be allocated scientifically and reasonably. Due to the complex underwater environment, the robustness in the search process should be considered for many influencing factors. Considering Using multiple AUVs to search multiple target areas, In this paper, an improved genetic algorithm is used for task allocation, and then the simulated annealing algorithm is used to plan the shortest path with reference to the multiple traveling salesman problem. The two algorithms are improved to improve the convergence speed, and finally use Matlab to simulate Verify the effectiveness of the improved algorithm.","PeriodicalId":230625,"journal":{"name":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computer, Blockchain and Financial Development (CBFD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBFD52659.2021.00061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the development of science and technology, the performance of autonomous underwater vehicles (AUV) has been continuously improved, and its application has become increasingly widespread, playing an important role in the military and civilian fields. AUV can perform underwater environmental reconnaissance, resource exploration, target search, and intelligence collection. In order to efficiently complete reconnaissance and search tasks, AUV resources need to be allocated scientifically and reasonably. Due to the complex underwater environment, the robustness in the search process should be considered for many influencing factors. Considering Using multiple AUVs to search multiple target areas, In this paper, an improved genetic algorithm is used for task allocation, and then the simulated annealing algorithm is used to plan the shortest path with reference to the multiple traveling salesman problem. The two algorithms are improved to improve the convergence speed, and finally use Matlab to simulate Verify the effectiveness of the improved algorithm.